SingleCellMapper 0.1.5
This vignette gives an overview of spatial data visualization with the SingleCellMapper package.
This document also introduces the ImageList class, which inherits from the SimpleList class.
Explain: images, masks, sce
Here, we will highlight the most simple use of the package
Load the libraries
Load the example data: SingleCellExperiment object
load("../data/pancreasSCE.RData")
pancreasSCE
## class: SingleCellExperiment
## dim: 5 282
## metadata(0):
## assays(2): counts exprs
## rownames(5): H3 SMA INS CD38 CD44
## rowData names(4): frame MetalTag Target clean_Target
## colnames(282): A02_imc.7 A02_imc.10 ... F01_imc.362 F01_imc.367
## colData names(10): ImageNb CellNb ... MaskName CellType
## reducedDimNames(0):
## spikeNames(0):
## altExpNames(0):
Load the example data: List of images
load("../data/pancreasImages.RData")
pancreasImages
## ImageList containing 3 image(s)
## names(3): A02_imc D01_imc F01_imc
## Each image contains 5 channel(s)
## channelNames(5): H3 SMA INS CD38 CD44
Load the example data: List of masks
load("../data/pancreasMasks.RData")
pancreasMasks
## ImageList containing 3 image(s)
## names(3): A02_mask D01_mask F01_mask
## Each image contains 1 channel(s)
Getting channel names
channelNames(pancreasImages)
## [1] "H3" "SMA" "INS" "CD38" "CD44"
plotPixel function
Figure 1: Quick start: plot pixel-level information
Figure 2: Quick start: plot cell masks
Figure 3: Quick start: plot specific channels
plotCells function
Figure 4: Quick start: plot cell-level information
Figure 5: Quick start: colour by cell type
Figure 6: Quick start: outline by cell type
Images should be stacks, all stacks should have the same number of channels
Masks should be single-channel images
Object should be a SingleCellExperiment
Introduction to the LoadImage function
mcols(pancreasImages)
## DataFrame with 3 rows and 1 column
## ImageNb
## <integer>
## A02_imc 1
## D01_imc 2
## F01_imc 3
mcols(pancreasMasks)
## DataFrame with 3 rows and 1 column
## ImageNb
## <integer>
## A02_mask 1
## D01_mask 2
## F01_mask 3
colData(pancreasSCE)$ImageNb
## [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [112] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [149] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3
## [186] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
## [223] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
## [260] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
Nicolas created SingleCellMapper - Nicolas and Nils implemented the package …
## R version 3.6.1 (2019-07-05)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.6 LTS
##
## Matrix products: default
## BLAS: /usr/lib/libblas/libblas.so.3.6.0
## LAPACK: /usr/lib/lapack/liblapack.so.3.6.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] parallel stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] SingleCellMapper_0.1.5 SingleCellExperiment_1.8.0
## [3] SummarizedExperiment_1.16.1 DelayedArray_0.12.2
## [5] BiocParallel_1.20.1 matrixStats_0.55.0
## [7] Biobase_2.46.0 GenomicRanges_1.38.0
## [9] GenomeInfoDb_1.22.0 IRanges_2.20.2
## [11] S4Vectors_0.24.3 BiocGenerics_0.32.0
## [13] EBImage_4.28.1 BiocStyle_2.14.4
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.3 locfit_1.5-9.1 lattice_0.20-40
## [4] fftwtools_0.9-8 png_0.1-7 assertthat_0.2.1
## [7] digest_0.6.24 R6_2.4.1 tiff_0.1-5
## [10] evaluate_0.14 ggplot2_3.2.1 highr_0.8
## [13] pillar_1.4.3 zlibbioc_1.32.0 rlang_0.4.4
## [16] lazyeval_0.2.2 raster_3.0-12 Matrix_1.2-18
## [19] rmarkdown_2.1 stringr_1.4.0 htmlwidgets_1.5.1
## [22] RCurl_1.98-1.1 munsell_0.5.0 compiler_3.6.1
## [25] xfun_0.12 pkgconfig_2.0.3 htmltools_0.4.0
## [28] tidyselect_1.0.0 tibble_2.1.3 gridExtra_2.3
## [31] GenomeInfoDbData_1.2.2 bookdown_0.17 codetools_0.2-15
## [34] viridisLite_0.3.0 crayon_1.3.4 dplyr_0.8.4
## [37] bitops_1.0-6 grid_3.6.1 gtable_0.3.0
## [40] lifecycle_0.1.0 magrittr_1.5 scales_1.1.0
## [43] stringi_1.4.6 XVector_0.26.0 viridis_0.5.1
## [46] sp_1.3-2 RColorBrewer_1.1-2 tools_3.6.1
## [49] glue_1.3.1 purrr_0.3.3 jpeg_0.1-8.1
## [52] abind_1.4-5 yaml_2.2.0 colorspace_1.4-1
## [55] BiocManager_1.30.10 knitr_1.28
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